Skip to search formSkip to main contentSkip to account menu
How to Understand and Assess a Theory: The Evolution of the SSTH into the GTVH and Now into the OSTH
The main thrust of this paper is to present to an important adjacent scholarly community of literary scholars how humor can be treated by the current strand of contemporary linguistics, or – more…
View via Publisher
On an Automatic Acquisition Toolbox for Ontologies and Lexicons in Ontological Semantics
Ontological semantic technology for detecting insider threat and social engineering
This paper describes a computational system for detecting unintentional inferences in casual unsolicited and unrestricted verbal output of individuals, potentially responsible for leaked classified…
View on ACM
Exploring BERT’s sensitivity to lexical cues using tests from semantic priming
TLDR
A case study analyzing the pre-trained BERT model with tests informed by semantic priming finds that BERT too shows “priming”, predicting a word with greater probability when the context includes a related word versus an unrelated one.
View on ACL
On Identifying Authors with Style
TLDR
A task to which stylometry is often applied: authorship attribution, the question of identifying or confirming the author of a text based on the known body of work is considered.
View on IEEE
Computational Semantic Detection of Information Overlap in Text
TLDR
This paper examines the use of the Ontological Semantic Technology (OST)—a modified version (Raskin et al 2010) ofOntological Semantics (Nirenburg & Raskin 2004)—for processing similar texts and compares it to human processing and shows that the machine matches four out of the five human findings.
Computationally Recognizing Wordplay in Jokes
Computationally Recognizing Wordplay in Jokes Julia M. Taylor (tayloj8@email.uc.edu) Lawrence J. Mazlack (mazlack@uc.edu) Electrical & Computer Engineering and Computer Science Department University…
Application-Guided Ontological Engineering
Understanding the unknown: Unattested input processing in natural language
TLDR
The paper describes the fuzzy approach to the problem within the framework of meaning based natural language processing with regard to the semantic and syntactic acceptability of a sentence.
View on IEEE
Predicting popular contributors in innovation crowds: the case of My Starbucks Ideas
TLDR
New empirical evidence is presented that reveals why some contributors' ideas are more viral than others in open crowds and suggests that companies can learn from popular contributors in ways that help them improve customer agility and better satisfy customers' needs.
View via Publisher
...
...
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License